{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Unnamed: 0              time   pool  max_used_capacity\n",
      "0           0  2018-07-30T12:00  tln32             7307.0\n",
      "1           1  2018-07-30T12:00  tam32               36.0\n",
      "2           2  2018-07-30T13:00  tln32             8984.0\n",
      "3           3  2018-07-30T13:00  tam32               31.0\n",
      "4           4  2018-07-30T14:00  tln32             8643.0\n",
      "len is 50\n",
      "--- tln32 ----\n",
      "    Unnamed: 0              time   pool  max_used_capacity\n",
      "0            0  2018-07-30T12:00  tln32             7307.0\n",
      "2            2  2018-07-30T13:00  tln32             8984.0\n",
      "4            4  2018-07-30T14:00  tln32             8643.0\n",
      "6            6  2018-07-30T15:00  tln32             6750.0\n",
      "8            8  2018-07-30T16:00  tln32             3280.0\n",
      "10          10  2018-07-30T17:00  tln32             1584.0\n",
      "12          12  2018-07-30T18:00  tln32             1471.0\n",
      "14          14  2018-07-30T19:00  tln32             1421.0\n",
      "16          16  2018-07-30T20:00  tln32             1130.0\n",
      "18          18  2018-07-30T21:00  tln32              719.0\n",
      "20          20  2018-07-30T22:00  tln32              516.0\n",
      "22          22  2018-07-30T23:00  tln32              383.0\n",
      "24          24  2018-07-31T00:00  tln32              316.0\n",
      "26          26  2018-07-31T01:00  tln32              311.0\n",
      "28          28  2018-07-31T02:00  tln32              306.0\n",
      "30          30  2018-07-31T03:00  tln32              281.0\n",
      "32          32  2018-07-31T04:00  tln32              437.0\n",
      "34          34  2018-07-31T05:00  tln32             1059.0\n",
      "36          36  2018-07-31T06:00  tln32             1494.0\n",
      "38          38  2018-07-31T07:00  tln32             3117.0\n",
      "40          40  2018-07-31T08:00  tln32             9163.0\n",
      "42          42  2018-07-31T09:00  tln32            11107.0\n",
      "44          44  2018-07-31T10:00  tln32            10461.0\n",
      "46          46  2018-07-31T11:00  tln32             8395.0\n",
      "48          48  2018-07-31T12:00  tln32             8688.0\n",
      "--- tam32 ----\n",
      "    Unnamed: 0              time   pool  max_used_capacity\n",
      "1            1  2018-07-30T12:00  tam32               36.0\n",
      "3            3  2018-07-30T13:00  tam32               31.0\n",
      "5            5  2018-07-30T14:00  tam32               19.0\n",
      "7            7  2018-07-30T15:00  tam32               18.0\n",
      "9            9  2018-07-30T16:00  tam32               31.0\n",
      "11          11  2018-07-30T17:00  tam32               19.0\n",
      "13          13  2018-07-30T18:00  tam32               31.0\n",
      "15          15  2018-07-30T19:00  tam32               31.0\n",
      "17          17  2018-07-30T20:00  tam32               22.0\n",
      "19          19  2018-07-30T21:00  tam32               21.0\n",
      "21          21  2018-07-30T22:00  tam32               22.0\n",
      "23          23  2018-07-30T23:00  tam32               21.0\n",
      "25          25  2018-07-31T00:00  tam32               19.0\n",
      "27          27  2018-07-31T01:00  tam32               21.0\n",
      "29          29  2018-07-31T02:00  tam32               31.0\n",
      "31          31  2018-07-31T03:00  tam32               21.0\n",
      "33          33  2018-07-31T04:00  tam32               21.0\n",
      "35          35  2018-07-31T05:00  tam32               21.0\n",
      "37          37  2018-07-31T06:00  tam32               31.0\n",
      "39          39  2018-07-31T07:00  tam32               31.0\n",
      "41          41  2018-07-31T08:00  tam32               31.0\n",
      "43          43  2018-07-31T09:00  tam32               19.0\n",
      "45          45  2018-07-31T10:00  tam32               19.0\n",
      "47          47  2018-07-31T11:00  tam32               28.0\n",
      "49          49  2018-07-31T12:00  tam32               21.0\n"
     ]
    },
    {
     "data": {
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x43XzzTdrwYIFsturb/OXlpbq8ccf1y233KKxY8dq06ZNTfkZAQAAANTB/245rOT0AkUG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\nERG57B+x9cpbsN6ZwwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1193b9780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--- dfOfPool <class 'pandas.core.series.Series'> ----\n",
      "pool\n",
      "tam32       36.0\n",
      "tln32    11107.0\n",
      "Name: max_used_capacity, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df = pd.read_csv('/workspace/logs/max_userd_capacity_AMS_ELS_20180731.csv')\n",
    "print(df.head())\n",
    "print(\"len is %d\" % len(df.index))\n",
    "\n",
    "dc = 'AMS'\n",
    "\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "plt.rcParams[\"font.size\"] =12\n",
    "fig = plt.figure(figsize=(16, 6))\n",
    "\n",
    "poolsDf = df['pool'].unique()\n",
    "\n",
    "\n",
    "i = 0\n",
    "for pool in poolsDf:\n",
    "    i = i + 1\n",
    "\n",
    "    poolDf = df.loc[df['pool'] == pool]\n",
    "\n",
    "    x = poolDf['time']\n",
    "    y = poolDf['max_used_capacity']\n",
    "    print(\"--- %s ----\" % pool)\n",
    "    print(poolDf)\n",
    "    \n",
    "    plt.xticks(rotation=30)\n",
    "    plt.plot(x, y, label=pool, marker='o', linestyle='solid', linewidth=2, markersize=6)\n",
    "\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "grouped = df['max_used_capacity'].groupby(df['pool'])\n",
    "dfOfPool = grouped.max()\n",
    "print(\"--- dfOfPool {} ----\".format(type(dfOfPool)))\n",
    "print(dfOfPool)\n",
    "df = dfOfPool.to_csv('/workspace/logs/max_userd_capacity_all_20180731.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
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